stor_tabel
Lærke
27/5/2022
## Filtration Time Recovery Species Rejection Std Type A_B
## 1 ID:8A 1 31.11111 Cl 6.550364 0.05323255 Authentic A
## 2 ID:8A 1 31.11111 SO4 72.826443 0.05069276 Authentic A
## 3 ID:8A 1 31.11111 Na 50.777842 0.01432982 Authentic A
## 4 ID:8A 1 31.11111 Ca 76.209133 0.05915190 Authentic A
## 5 ID:8A 1 31.11111 SiO2 30.316249 0.07493814 Authentic A
## System
## 1 Pilot_scale
## 2 Pilot_scale
## 3 Pilot_scale
## 4 Pilot_scale
## 5 Pilot_scale
## Filtration Time Stream Recovery Species Concentration Std Plot
## 1 ID:8A 1 Feed 31.11111 Cl 4.2796487 0.051321817 <NA>
## 2 ID:8A 1 Feed 31.11111 SO4 1.4695491 0.046913078 <NA>
## 3 ID:8A 1 Feed 31.11111 Na 26.4620010 0.004920126 <NA>
## 4 ID:8A 1 Feed 31.11111 Ca 0.7699627 0.034253092 <NA>
## 5 ID:8A 1 Feed 31.11111 SiO2 1.5579228 0.021367521 <NA>
## Mw Type System
## 1 Ca, Cl, SiO2, SO4 Authentic Pilot_scale
## 2 Ca, Cl, SiO2, SO4 Authentic Pilot_scale
## 3 Na Authentic Pilot_scale
## 4 Ca, Cl, SiO2, SO4 Authentic Pilot_scale
## 5 Ca, Cl, SiO2, SO4 Authentic Pilot_scaleConcentration of filtraiton A divided into cations and anions.
Ion_data_frame = data.frame()
## SPRR data håndtering
SPRR = read.table(file='data/SPRR_df.csv', header = T,sep = "\t",stringsAsFactors = T)
SPRR_pH= c(NA,9.37,9.26,NA,9.26,9.35,NA,9.67,9.68,NA,9.56,9.66,NA,9.83,9.89,NA,9.81,9.87)
SPRR_con= c(NA,2350,1670,NA,2330,1680,NA,2440,1750,NA,2510,1760,NA,2450,1840,NA,2540,1830)
#SPRR_type=rep(c("SPRR"),each=18)
SPRR_names = c("SPRR_1","SPRR_2","SPRR_3","SPRR_4","SPRR_5","SPRR_6","SPRR_7","SPRR_8","SPRR_9","SPRR_10","SPRR_11","SPRR_12","SPRR_13","SPRR_14","SPRR_15","SPRR_16","SPRR_17","SPRR_18")
SPRR_wrangle = cbind(SPRR%>%filter(Stream == "Feed"),SPRR%>%filter(Stream == "Rejection")%>%select("Na","Ca","Cl","SO4","SiO2","HCO3"))
SPRR_wrangle$pH = SPRR_pH
SPRR_wrangle$con = SPRR_con
#SPRR_wrangle$type = SPRR_type
colnames(SPRR_wrangle) = c("name","Stream","Cl_ratio","SiO2_teo","pH","Ca","Na","Cl","SO4","SiO2_mgL","HCO3","Rej_Na","Rej_Ca","Rej_Cl","Rej_SO4","Rej_SiO2","Rej_HCO3","Conductivity")
SPRR_wrangle$name = SPRR_names
SPRR_clean = SPRR_wrangle%>%select(-c("Stream","SiO2_teo","HCO3","Rej_HCO3","Cl_ratio"))
SPRR_clean$state = "Steady State"
SPRR_clean$type = "SPRR"
SPRR_clean$pH[1]=9.33
SPRR_clean$time=NA
SPRR_clean$start_vol = NA
###multisalt håndtering
M_9.2 = read.table(file='data/M9.2_df.csv', header = T,sep = "\t",stringsAsFactors = T)
M_9.2_clean = M_9.2%>%select(-c("time","conductivity"))
M_9.2_clean$Conductivity = c(1560,1730,1880,2080,2390,2700)
M_9.2_clean$state = "Batch"
M_9.2_clean$type = "multi"
M_9.2_clean$name = c("M_9.2_3.5h","M_9.2_5h","M_9.2_6h","M_9.2_7h","M_9.2_8h","M_9.2_8.7h")
M_9.2_clean$time = c(3.5,5,6,7,8,8.7)
M_9.2_clean$start_vol = 10
M_10 = read.table(file='data/M10_df.csv', header = T,sep = "\t",stringsAsFactors = T)
M_10_clean = M_10%>%select(-c("time"))
M_10_clean$Conductivity = c(1830,2050,2350,2550,2830,3250)
M_10_clean$state = "Batch"
M_10_clean$type = "multi"
M_10_clean$pH = c(10.13,10.15,10.17,10.19,10.21,10.24)
M_10_clean$name = c("M_10_3h","M_10_4h","M_10_5h","M_10_5.5h","M_10_6h","M_10_6.5h")
M_10_clean$time = c(3,4,5,5.5,6,6.5)
M_10_clean$start_vol = 8.5
M_10.5 = read.table(file='data/M10.5_df.csv', header = T,sep = "\t",stringsAsFactors = T)
M_10.5_clean = M_10.5%>%select(-c("time"))
M_10.5_clean$Conductivity = c(2080,2390,2660,3020,3570,4470)
M_10.5_clean$state = "Batch"
M_10.5_clean$type = "multi"
M_10.5_clean$pH = c(10.5,10.52,10.54,10.56,10.59,10.63)
M_10.5_clean$name = c("M_10.5_2.5h","M_10.5_4h","M_10.5_5h","M_10.5_6h","M_10.7h","M_10.5_8h")
M_10.5_clean$time = c(2.5,4,5.5,6,7,8)
M_10.5_clean$start_vol = 10
### ICR data
ICR_1 = read.table(file='data/ICR_df.csv', header = T,sep = "\t",stringsAsFactors = T)
colnames(ICR_1) = c("name","SiO2_mgL","Na","Cl","SO4","Ca","pH","Rej_Cl","Rej_SO4","Rej_Na","Rej_Ca","Rej_SiO2","state")
ICR_clean = ICR_1
ICR_clean$Conductivity = c(2477,2517,2570,2625,2685,2740,2810,2881,2951,3040,3126,3221,3376,3568,4019)
SPRR_clean$Conductivity[1]=4210
ICR_clean$type = "ICR"
ICR_clean$time = c(20/60,40/60,60/60,80/60,100/60,2,140/60,160/60,3,200/60,220/60,240/60,270/60,300/60,360/60)
ICR_clean$start_vol = 10
###Sættes sammen
col_order <- c("name","Na","Cl","SO4","Ca","SiO2_mgL","pH","Rej_Cl","Rej_SO4","Rej_Na","Rej_Ca","Rej_SiO2","state","type","time","start_vol")
M_9.2_clean = M_9.2_clean[,col_order]
M_10_clean = M_10_clean[,col_order]
M_10.5_clean = M_10.5_clean[,col_order]
SPRR_clean = SPRR_clean[,col_order]
ICR_clean = ICR_clean[,col_order]
Ion_data_frame = rbind(M_9.2_clean,M_10_clean,M_10.5_clean,SPRR_clean,ICR_clean)
Ion_data_frame[1:18,8:12] = Ion_data_frame[1:18,8:12]*100
Mw_Cl=35.45
Mw_Na=22.99
Mw_Ca=40.078
Mw_SO4=96.06
Mw_SiO2=60.08
Ion_data_frame = Ion_data_frame%>%mutate("Na_mmol"=Na/Mw_Na)
Ion_data_frame = Ion_data_frame%>%mutate("Ca_mmol"=Ca/Mw_Ca)
Ion_data_frame = Ion_data_frame%>%mutate("Cl_mmol"=Cl/Mw_Cl)
Ion_data_frame = Ion_data_frame%>%mutate("SO4_mmol"=SO4/Mw_SO4)
Ion_data_frame = Ion_data_frame%>%mutate("SiO2_mmol"=SiO2_mgL/Mw_SiO2)
### noget med recovery
Ion_data_frame = Ion_data_frame%>%mutate("perm_vol"=time*1.02)
Ion_data_frame = Ion_data_frame%>%mutate("Recovery"=100*(1-(start_vol-perm_vol)/start_vol))
#Udtryk for ladning af silica som funk af pH, jeg kan ikkehuske hvor det kommer fra
a=1.00016
b=2.314233
c=9.831689
Ion_data_frame = Ion_data_frame%>%mutate(SiO2_ladet = a/(1+exp(-b*(pH-c))))
#Ion_data_frame = Ion_data_frame%>%mutate(SiO2_ladet1=-0.0052*pH^5+0.2074*pH^4-3.2404*pH^3+24.84*pH^2-93.425*pH+137.74) #Gammelt udtryk for samme
Ion_data_frame = Ion_data_frame%>%mutate(Cl_SO4 = Cl_mmol/(Cl_mmol+SO4_mmol))
Ion_data_frame = Ion_data_frame%>%mutate(total_sio2_ladet=SiO2_mmol*SiO2_ladet)
Ion_data_frame = Ion_data_frame%>%mutate(anion_total = total_sio2_ladet+SO4_mmol+Cl_mmol)
Ion_data_frame = Ion_data_frame%>%mutate(Cl_anion = Cl_mmol/anion_total)
FCT_data=read.table(file='data/FCT_stor_tabel.csv',header= T,sep="\t")
pilot_data=read.table(file='data/pilot_stor_tabel.csv',header= T,sep="\t")
ICR_data=read.table(file='data/ICR_stor_tabel.csv',header= T,sep="\t")
Ion_data_frame = rbind(Ion_data_frame,FCT_data)
Ion_data_frame = rbind(Ion_data_frame,pilot_data)
Ion_data_frame = rbind(Ion_data_frame,ICR_data)
pH_FCT=c(9.77,9.92,9.65,9.78,8.28,8.5,8.87,8.89)
pH_pilot=c(9.86,9.81,9.85,9.92,10.03,10.15,8.84,8.87,8.92,9.0,9.12)
pH_ICR=c(7.9,7.88,7.91,7.92,9.81,9.82,9.85,9.89)
Ion_data_frame$pH[52:59]=pH_FCT
Ion_data_frame$pH[60:70]=pH_pilot
Ion_data_frame$pH[71:78]=pH_ICR
Ion_data_frame$name[37:51]="ID:4A"
Ion_data_frame$name[1:6]="ID:1"
Ion_data_frame$name[7:12]="ID:2"
Ion_data_frame$name[13:18]="ID:3"
Ion_data_frame$name[19:36]="SS"
Ion_data_frame$name[52:59]=c("ID:6A","ID:6A","ID:7A","ID:7A","ID:6B","ID:6B","ID:7B","ID:7B")
Ion_data_frame = Ion_data_frame%>%mutate(SiO2_ladet = a/(1+exp(-b*(pH-c))))
Ion_data_frame = Ion_data_frame%>%mutate(Cl_SO4 = Cl_mmol/(Cl_mmol+SO4_mmol))
Ion_data_frame = Ion_data_frame%>%mutate(total_sio2_ladet=SiO2_mmol*SiO2_ladet)
Ion_data_frame = Ion_data_frame%>%mutate(anion_total = total_sio2_ladet+SO4_mmol+Cl_mmol)
Ion_data_frame = Ion_data_frame%>%mutate(Cl_anion = Cl_mmol/anion_total)
Ion_data_frame%>%filter(name!="ID:4B",name!="ID:5B",name!="ID:6B",name!="ID:7B",name!="ID:8B")%>%
ggplot(aes(x=Cl_SO4,y=Rej_Cl,color=name))+
geom_point()+geom_line()+#scale_color_manual(labels = ioner, values =colors2)+
geom_hline(yintercept=0)+
theme(legend.text.align=0)+
facet_grid(cols=vars(type),scale="free")
Ion_data_frame%>%filter(name!="ID:4B",name!="ID:5B",name!="ID:6B",name!="ID:7B",name!="ID:8B")%>%
ggplot(aes(x=Cl_anion,y=Rej_Cl,color=name))+
geom_point()+geom_line()+#scale_color_manual(labels = ioner, values =colors2)+
geom_hline(yintercept=0)+
theme(legend.text.align=0)+
facet_grid(cols=vars(type),scale="free")
Ion_data_frame%>%filter(name!="ID:4B",name!="ID:5B",name!="ID:6B",name!="ID:7B",name!="ID:8B")%>%
ggplot(aes(x=SiO2_ladet/anion_total,y=Rej_SiO2,color=name))+
geom_point()+geom_line()+#scale_color_manual(labels = ioner, values =colors2)+
geom_hline(yintercept=0)+
theme(legend.text.align=0)+
facet_grid(cols=vars(type),scale="free")
Ion_data_frame%>%filter(name!="ID:4B",name!="ID:5B",name!="ID:6B",name!="ID:7B",name!="ID:8B")%>%
ggplot(aes(x=SO4_mmol,y=Rej_SiO2,color=name))+
geom_point()+geom_line()+#scale_color_manual(labels = ioner, values =colors2)+
geom_hline(yintercept=0)+
theme(legend.text.align=0)+
facet_grid(cols=vars(type),scale="free")
Nu med multiple regression